考虑动态临界加速度的地震边坡永久位移预测模型研究

在区域边坡地震危险性评价中主要采用永久位移预测模型进行地震边坡永久位移计算。永久位移预测模型以Newmark滑块理论为基础,通过大量实测地震时程记录统计拟合得出。针对Newmark理论中滑动面抗剪强度参数保持不变和已有位移预测模型的计算位移小于实测位移的问题,利用动态临界加速度理论,分别构建含有峰值加速度和阿里亚斯强度的两种位移预测模型。对该模型计算出的永久位移合理性进行讨论,发现永久位移计算结果符合滑坡实测位移的数量级。采用本文模型计算的永久位移更加接近地震滑坡位移实际大小,可以解决一直存在的预测位移小于实测位移的问题。在更进一步讨论发展的基础上,本文模型可满足更多的理论应用和工程实际,为区域边坡地震危险性评价提供思路。     

基于降雨入渗的Newmark模型改进及地震滑坡危险性预测研究

滑坡是一种破坏性非常强的地质灾害,其中地震与降雨均为诱导滑坡发生的关键因素。从降雨期间发生地震的角度考虑,基于Green-Ampt降雨入渗模型对Newmark模型进行改进,推导两因素耦合作用下的边坡安全系数F_S。以云南省鲁甸县某一区域为例,分别开展无降雨、降雨无积水与降雨积水三种情况下的地震滑坡危险性预测及坡度与入渗深度因子对位移影响分析。通过比较上述三种情况,得到研究区域内的Newmark累积位移分布及危险性区划。结果表明：与未降雨情况相比,后两种情况下地震滑坡高危险程度区域面积占比计算区域随着降雨时间的增加从1%分别提高至9%、12%,滑坡低危险程度区域面积从51%分别降低至35%、33%;坡度值与入渗深度值越大,滑坡位移越大,危险性越高。Newmark改进模型充分考虑了降雨对地震滑坡产生的促进作用,能更好地反映出研究区每个场点相对的滑坡危险性,对滑坡危险性预测具有一定指导意义。     

土质边坡地震动力响应特性分析及稳定性评价

地震触发滑坡是一种常见的地震次生灾害。据相关研究显示,全球范围的滑坡带分布与地震带的分布具有惊人的一致性,可见地震对引发滑坡的作用之大。因此,边坡在地震作用下的稳定性研究成为了一个倍受相关专家关注的问题。由于边坡自身材料性质的不确定性,尤其是土质边坡,导致在原本复杂的地震作用下的研究变得更加困难。为解决这一问题,本文以土质边坡为研究对象,综合考虑土坡自身和地震动两方面特性来分析评价土坡的地震动力响应规律和稳定性。主要研究成果如下:(1)地震动特性对边坡稳定性的影响规律研究。选取不同幅值、频谱和持时的地震动加速度时程作为荷载输入,模拟分析不同地震动特性对土质边坡响应的影响规律,分析结果表明,幅值、频谱和持时地震动三要素对土坡稳定性均有重要影响;(2)地震作用土质边坡类型划分的研究。利用层次分析法确定影响地震边坡各因素的作用权重,并选取权重较高的影响因素作为划分依据,将地震作用土质边坡类型综合划分为4类。每个类型中又根据坡度的不同划分为缓坡、缓陡坡、陡坡和急坡4个小类;(3)基于有限元强度折减法,本文对土质边坡地震作用下稳定性状态判定方法进行了研究。定义了等效塑性应变区贯通程度的概念,建立了等效塑性应变区贯通程度与边坡安全系数的对应关系,并提出利用等效塑性应变区贯通程度作为边坡稳定性判断依据的方法;(4)地震作用下各类土质边坡稳定性评价与预测应用分析。模拟计算了不同地震动作用下各类土质边坡的稳定性,应用论文提出的方法对各类土质边坡的地震危险性进行了评价与预测,并选取实际发生的地震滑坡与本文预测评价的结果作对比,验证了本文预测评价结果的准确性。     

基于简化纽马克位移模型的地震滑坡岩土体强度参数研究

本文以2008年汶川M_S8.0地震的烈度数据为基础,采用简化纽马克法对四川省青川县不同岩组的岩土体强度参数组合所对应的滑坡位移进行计算得到滑坡危险性等级图,并以计算得到的预测滑坡区与实际调查的滑坡数据的吻合度作为评价标准,对研究区内岩土体强度参数进行分析。分析结果表明,研究区大部分区域岩组的岩土体强度参数的合理取值区间与 《工程岩体分级标准GB 50218—94》 建议的参数取值范围基本一致,而本文在此基础上所确定的取值结果,在一定程度上可以提高地震滑坡危险性评估的精度。      

基于信息量和逻辑回归耦合模型的黄土地震滑坡危险性分析

黄土地震滑坡危险性分析对黄土地区城镇化、工程建设的规划和地震灾害预防具有重要意义。以甘肃省定西市岷县—漳县交界处为研究区域,通过统计分析该区历史地震滑坡灾害数据,归纳并建立包含地震、坡度、坡高、坡向、地层岩性、年平均降雨量、河流流域和地貌类型等8个影响因子的评价指标体系,采用信息量模型、逻辑回归模型和信息量-逻辑回归耦合模型分别分析该区域黄土地震滑坡危险性。结果表明：(1)地震、河流和降雨是诱发黄土滑坡灾害发生的主要因素,其中地震因子贡献率最大;(2)研究区可划分为高、较高、中、低和极低危险区五个等级,其中高危险区主要集中于岷县、漳县与陇西县等地;(3)根据受试者工作特性(ROC)曲线精度检验结果,三种模型的AUC值分别为0.889、0.617和0.898,信息量-逻辑回归耦合模型结果的精确性相比其他两个模型更高。     

基于修正岩土体强度参数的简化纽马克位移法地震滑坡危险性快速评估技术

地震滑坡危险性评估可为震后应急响应等提供科学的决策依据。纽马克位移法可不依赖同震滑坡编目快速评估同震滑坡危险性。工程岩体物理力学参数是该方法的核心参数之一,但其赋值过于单一,难以反映复杂地质背景下岩体强度的空间差异性。针对上述问题,本文在分析地震滑坡影响因子的基础上,选择距断层距离、高程和距水系距离作为影响岩体强度的评价指标并建立岩体强度评价模型,获得区域岩体强度修正系数,进而修正传统方法的临界加速度。结合震后的即时地震动峰值加速度,采用简化纽马克位移法计算边坡累积位移,开展地震滑坡危险性快速评估,并以汶川M_W7.9地震的地震滑坡危险性评估为例验证本文方法。结果表明,相对于传统方法,本文方法划分的地震滑坡危险区与同震滑坡分布更加一致。      

潜在地震滑坡危险区区划方法

不同地区地震活动的强度和频率是不同的.基于地震危险性分析的地震滑坡危险研究在综合了地震烈度、位置、复发时间等因素的基础上,考虑了地震动峰值加速度时空分布的特点,可以有效地应用于潜在地震滑坡危险区区划.以汶川地震灾区为研究对象,根据研究区的地质构造、地震活动特点等划分出灾区的潜在震源区,对该区进行地震危险性分析,并在此基础上采用综合指标法做出基于地震危险性分析的地震滑坡危险性区划.所得地震滑坡危险性区划按照滑坡危险程度分为高危险、较高危险、较低危险和低危险四级,表示未来一段时间内研究区在遭受一定超越概率水平的地震动作用下,不同地区地震滑坡发生的可能程度. 本文给出的地震滑坡危险性区划结果中,汶川地震滑坡崩塌较发育的汶川、北川、茂县等部分区域均处于高危险或较高危险区域;在对具有较高DEM精度的北川擂鼓镇地区所作的地震滑坡危险性区划中,汶川地震中实际发生的地震滑坡灾害与地震滑坡危险区划结果表现出较好的一致性.对区域范围而言,基于地震危险性分析的地震滑坡区划,可为初期阶段的土地规划使用及重大工程选址提供参考.     

基于Newmark方法的四川芦山6.1级地震公路滑坡快速评估

2022年6月1日四川省雅安市芦山县6.1级地震发生后,基于地震震级与历次地震中震区交通状况综合考虑,对震区公路滑坡风险等级开展快速评估工作,使用Newmark模型计算得到研究区内岩土体永久累积位移并划定地震滑坡风险等级。结果显示,在芦山6.1级地震的影响下,研究区内滑坡风险等级由震中区域向四周逐渐降低,与地震动强度的衰减具有相似的规律;区内北西侧的滑坡风险等级要明显高于南东侧,该分布规律与研究区地形地貌特征相吻合;依据划定的危险性等级,在研究区圈定7个公路滑坡高风险区域,收集到的实际7处受灾路段有6处落在公路滑坡高风险区内。验证表明,基于Newmark模型与路网数据划定的公路滑坡高风险区具有较高的可信度,该地震公路滑坡快速评估方法可以为灾后应急救援力量部署及减轻地质灾害造成的损失提供一定帮助。     

黄土高原地震作用下黄土滑坡滑距预测方法

为评估黄土高原地区地震滑坡致灾区域,提出一种基于模糊信息优化处理的地震滑坡滑距预测方法。在野外调查、室内试验和分析的基础上,对黄土高原的地震滑坡类型、性质和影响因素进行分析。以摩根斯坦-普莱斯法计算黄土边坡的稳定性,建立边坡最小安全系数与影响因素的关系,其影响因素主要包括地震烈度、比高、坡角、容重、内黏聚力、内摩擦角等,并在此基础上得到纯黄土地震滑坡滑距的影响关系。将黄土高原地区数次大震中采集到的93个样本数据进行归纳分析,建立模糊信息优化处理模型。所得的计算结果通过误差校验和与其他滑坡滑距预测方法进行对比,来证明本模型有较高的准确性。最后对天水市22个潜在滑坡的边坡进行滑距预测。     

地震诱发滑坡的危险性分析与预测

结合地震滑坡的特点和相关文献研究,介绍了地震力的分析方法、地震滑坡的机理、地震危险性分析的方法、地震活动性参数的确定方法以及场点地震危险性概率计算原则。将两种地震诱发滑坡预测结果进行对比,分析结果表明,地震滑坡危险区主要集中在中国西部地区（川、滇、甘、陕、新疆等省区）及中国台湾地区,随预测年限的增加场地的地震滑坡危险性也随之增高,地震崩塌滑坡的危险区域明显加大。     

一种适用于黄土斜坡地震稳定性快速评估的综合判别方法——以宁夏西吉县为例

选取宁夏西吉县为目标区,对区内1920年海原8.5级特大地震所诱发的347处黄土地震滑坡进行野外调查,获取了详实的基础数据.在此基础上结合遥感影像解译,总结了研究区内黄土地震滑坡的分布特征,并依此提出了宏观、定性的黄土斜坡地震稳定性快速判别方法.基于分布特征选取了坡高、坡角、坡向及地震动强度作为基本参数,应用MLP神经...     

断裂性质与滑坡分布的关系——以汶川地震中的大型滑坡为例

越来越多的地震滑坡相对于地震断层的不对称分布震例让人们意识到断层上盘效应的存在。 然而,目前有关断裂运动方式与滑坡空间分布关系的研究还不够充分和深入。在收集大量地震滑坡震例资料并获得其分布规律的基础上,建立了一个简化的断层模型,以地震波在地表与断层面之间反射传播特性为基础,探讨断层倾角改变对地表地震动强度的影响。进而,以汶川地震触发的大型滑坡为例,研究了断层的几何特征和运动方式对诱发滑坡空间分布的影响。结果表明,断层的倾角对滑坡空间分布范围具有控制作用,随着倾角的增加,垂直断层走向的滑坡分布范围逐渐减小;并且,大型滑坡的初始坡面受到断裂运动方向的影响,与断裂运动方向一致的坡面更容易发生滑坡。所获结果不仅有助于提高区域性地震滑坡危险区域的预测精度,而且对认识大型滑坡的滑动机制、主控因素以及可能的滑动规模、滑距等也起到促进作用。通过对滑坡崩塌的认识来辅助提高对地质构造、地震断层等的认识,应是地震诱发滑坡崩塌研究的新的意义所在。     

GIS支持下的地震诱发滑坡危险区预测研究

为了满足对地震诱发滑坡危险区预测的不断增长的迫切要求，灾害评价成为帮助决策过程重要的基础工具之一。即使地震滑坡危险性各组份的评价很困难，但地理信息可辅助提出这种灾害制图的有关方法。描述了用于地理信息系统识别和定量计算不同地震滑坡危险区的技术方法，确定了地震烈度、地形坡度、岩土体类型和现存滑坡密度共4个因子参与的地震诱发滑坡危险性分析。在ARC／INFO DRID支持下，进行叠合分析，由此编制了云南省地震诱发滑坡危险区预测图。由地貌学家提出的地震诱发滑坡预测为规划和工程师提供了对区域规划和建筑工程有价值的技术方法。     

Distribution of Landslides in Baoshan City, Yunnan Province, China

Using Google Earth software as a platform, this study has established an integrated database of both old and new landslides in Baoshan City, Yunnan Province, China, and analyzed their development characteristics together with distribution rules, respectively. Based on the results, a total of 2 427 landslides occurred in the study area, including 2 144 new landslides and 283 old landslides, with a total area of about 104.8 km². The new landslides are mostly in small-scales with an area less than 10 000 m², while the area of individual old landslide is mostly larger than 10 000 m². By analyzing the relationship between the two types of landslides and eight impact factors (i.e., elevation, slope angle, slope aspect, slope position, lithology, fault, regional Peak Ground Acceleration (PGA), and average annual rainfall), the different individual influencing factors, distribution regularities and mechanisms of the two types of landslides are revealed. In detail, the main influencing factors of new landslides are elevation, slope angle, slope aspect, slope position, lithology, regional PGA and average annual rainfall, while the influencing factors of old landslides are mainly elevation, slope angle, and lithology. This study provides basic data and support for landslide assessment and further disaster reduction in Baoshan City. Besides, it also provides new constraints in deeply understanding the effect of different topographic and geological conditions, historical earthquakes, rainfall and other factors on the occurrence mechanisms of both new landslides and old landslides.     

Fully probabilistic seismic displacement analysis of spatially distributed slopes using spatially correlated vector intensity measures

Earthquake‐induced slope displacement is an important parameter for safety evaluation and earthquake design of slope systems. Traditional probabilistic seismic hazard analysis usually focuses on evaluating slope displacement at a particular location, and it is not suitable for spatially distributed slopes over a large region. This study proposes a computationally efficient framework for fully probabilistic seismic displacement analysis of spatially distributed slope systems using spatially correlated vector intensity measures (IMs). First, a spatial cross‐correlation model for three key ground motion IMs, that is, peak ground acceleration (PGA), Arias intensity, and peak ground velocity, is developed using 2686 ground motion recordings from 11 recent earthquakes. To reduce the computational cost, Monte Carlo simulation and data reduction techniques are utilized to generate spatially correlated random fields for the vector IMs. The slope displacement hazards over the region are further quantified using empirical predictive equations. Finally, an illustrative example is presented to highlight the importance of the spatial correlation and the advantage of using spatially correlated vector IMs in seismic hazard analysis of spatially distributed slopes. Copyright © 2013 John Wiley & Sons, Ltd.     

汶川地震滑坡危险性评价——以武都区和文县为例

利用GIS技术详细研究汶川地震在甘肃省陇南市武都区和文县触发的滑坡地质灾害的分布规律及其与地震烈度、地形坡度、断层、高程、地层岩性的相关关系,采用基于GIS的加权信息量模型的崩塌滑坡危险性评价方法,对研究区的地震滑坡危险性进行学科分析。结果表明：极高危险区在高程上主要分布在集水高程区,高度危险区主要沿白水江、白龙江等主干河流两侧极高易发区的边界向两侧扩展,轻度和极轻度危险区面积占比较小,主要分布在低烈度、活动断裂不发育、人类活动微弱的高海拔地区,另外国道G215沿极高危险性区域分布明显;利用危险性等级分区结果统计人口公里格网数据,得到武都区和文县潜在影响人口,发现研究区约78万人将受到地震滑坡灾害的潜在影响。     

Real-time mapping of earthquake-induced landslides

Rigid sliding block analysis is a common analytical procedure used to predict the potential for earthquake-induced landslides for natural slopes. Currently, predictive models provide the expected level of displacement as a function of the characteristics of the slope (e.g., geometry, strength, yield acceleration) and the characteristics of earthquake shaking (e.g., peak ground acceleration, peak ground velocity). These predictive models are used for developing seismic landslide hazard maps which identify zones with risk of earthquake-induced landslides. Alternatively, these models can be combined with Shakemaps to generate “near-real-time” Slidemaps which could be used, among others, as a tool in disaster management. Shakemaps (a publicly available free service of the United States Geological Survey, USGS) provide near-real-time ground motion conditions during the time of an earthquake event. The ground motion parameters provided by a Shakemap are very useful for the development of Slidemaps. By providing ground motion parameters from an actual earthquake event, Shakemaps also serve as a tool to decouple the uncertainty of the ground motion in sliding displacements prediction. Campania region in Italy is studied for assessing the applicability of using Shakemaps for regional landslide-risk assessment. This region is selected based on the availability of soil shear strength parameters and the proximity to the 1980 Irpina (M _w  = 6.9) Earthquake.     

Hazard Assessment of Co-seismic Landslides Based on Information Value Method: A Case in 2018 MW6.6 Hokkaido Earthquake, Japan

An M_W6.6 earthquake occurred in eastern Hokkaido, Japan on September 6^th, 2018. Based on the pre-earthquake image from Google Earth and the post-earthquake image from high resolution (3 m) planet satellite, we manually interpret 9 293 coseismic landslides and select 7 influencing factors of seismic landslide, such as elevation, slope, slope direction, road distance, flow distance, peak ground acceleration (PGA) and lithology. Then, 9 293 landslide points are randomly divided into training samples and validation samples with a proportion of 7:3. In detail, the training sample has 6 505 landslide points and the validation sample has 2 788 landslide points. The hazard risk assessment of seismic landslide is conducted by using the information value method and the study area is further divided into five risk grades, including very low risk area, low risk area, moderate risk area high risk area and very high risk area. The results show that there are 7 576 landslides in high risk area and very high risk area, accounting for 81.52% of the total landslide number, and the landslide area is 22.93 km², accounting for 74.35% of the total area. The hazard zoning is in high accordance with the actual situation. The evaluation results are tested by using the curve of cumulative percentage of hazardous area and cumulative percentage of landslides number. The results show that the success rate of the information value method is 78.50% and the prediction rate is 78.43%. The evaluation results are satisfactory, indicating that the hazard risk assessment results based on information value method may provide scientific reference for landslide hazard risk assessment as well as the disaster prevention and mitigation in the study area.     

INVESTIGATION TO LANDSLIDES TRIGGERED BY THE 1856 QIANJIANG-XIANFENG(DALUBA)EARTHQUAKE AND THEIR GENERATION MECHANISMS

On 10 June 1856, an M61/4 earthquake occurred between Qianjiang, Chongqin and Xianfeng, Hubei, resulting in severe geologic hazard including a series of large-scale landslides. Based on previous work, combining field investigations and remote sensing imagery, we have mapped the locations of three landslides triggered by this event, dominated by slumps. Our field work included observations to every failure slopes and occurrence, lithology and joints of rocks in the surroundings. We also employed an unmanned air plane to take pictures of the study area, yielding high-resolution DEM and DOM data which permit to generate terrain contours with a 2m interval. With these field investigations, we have described the sizes and forms of each slump mass in detail, and studied their generation mechanisms. Our research suggests the following natural conditions are responsible for these seismic landslides. 1)In a tectonic stress field characterized by NW-SE directed principal compressive stress, the slopes received a seismic acceleration from NW to SE in a short time. 2)Strata dip in a direction consistent with the seismic motion, thus the slope was easy to slide along stratum interfaces. 3)The two sets of joints existing in rocks experienced long-term weathering, resulting in connection of partial structural planes and destruction to the intactness of rock bodies.